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作者：FAN, JQ; HECKMAN, NE; WAND, MP
作者单位：University of British Columbia; University of New South Wales Sydney
摘要：We investigate the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight to generalized linear models and quasi-likelihood contexts. In the ordinary regression case, local polynomial fitting has been seen to have several appealing features in terms of intuitive and mathematical simplicity. One noteworthy feature is the better performance near the boundaries compared to the traditional kernel regression estimators. These properties are shown to car...
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作者：HUGHES, MD; THOMPSON, SG; POCOCK, SJ
作者单位：University of London; London School of Hygiene & Tropical Medicine
摘要：Any screening program based on a quantitative risk factor has the objective of identifying individuals at high risk of disease. When the risk factor varies within individuals over time or is subject to measurement error, repeat measurements should aid risk assessment. This article presents statistical guidelines for sequential screening based on measurements accumulated over time. The aim for each subject is to decide whether (a) risk is sufficiently low that screening can be stopped, or (b) r...
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作者：KOOPERBERG, C; STONE, CJ; TRUONG, YK
作者单位：University of California System; University of California Berkeley; University of North Carolina; University of North Carolina Chapel Hill
摘要：Linear splines and their tenser products are used to estimate the conditional log-hazard function based on possibly censored, positive response data and one or more covariates. An automatic procedure involving the maximum likelihood method, stepwise addition, stepwise deletion, and the Bayes Information Criterion is used to select the final model. The possible models contain proportional hazards models as a subclass, which makes it possible to diagnose departures from proportionality. Cubic sp...
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作者：SOLOW, AR
摘要：This article describes an exploratory analysis of a record of major El Nino events covering the period 1800-1987. This record contains both the years during which the events occurred and a binary indication of their magnitude. The record is modeled as a marked point process in which the times of the events follow a renewal process and the sequence of binary marks follows a stationary first-order Markov chain.
